Risultati della simulazione

In Tab. V, sono sono raccolte le coordinate geografiche di siti campione su cui sono state condotte le simulazioni, e la specie agricole ivi presenti. In Fig. 6.6 sono mostrate le serie storiche FAO dei livelli di produzione (valori medi per il Kenya) delle due specie agricole analizzate; evidenziati in giallo, i valori relativi all’anno 2015 relativi alle simulazioni condotte, appaiono del tutto coerenti con i valori di riferimento medi presentati. In Tab.VI sono invece disponibili i rapporti completi relativi alle simulazioni condotte; è possibile vedere come non siano stati presi in considerazione fattori di stress come la salinizzazione del suolo o particolari deficit della fertilità del terreno. Tuttavia fattori di stress termico, come pure elevati livelli di sofferenza al livello foliare e degli stomi, sono determinanti nel determinare una drastica riduzione dell’HI, da valori di riferimento prossimi al 48%, sino a valori del 18-23%.

Tabella V Siti campione

Sample Type Lon Lat

Sample field n. 1 Maize 35.92187 E 0.30612 N

Sample field n. 2 Maize 35.94662 E 0.34212 N

Sample field n. 3 Maize 35.92412 E 0.35112 N

Sample field n. 4 Maize 35.92412 E 0.35337 N

Sample field n. 5 Wheat 35.92187 E 0.30612 N

Sample field n. 6 Wheat 35.94212 E 0.34662 N

Sample field n. 7 Wheat 35.94662 E 0.34662 N

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Tabella VI

Sintesi simulazioni AquaCrop

s.f. 1 s.f. 2 s.f. 3 s.f. 4 s.f. 5 s.f. 6 s.f. 7 Day1 22 22 7 15 1 1 15 Month1 3 3 4 3 3 3 3 Year1 2015 2015 2015 2015 2015 2015 2015 Rain mm 190 190 176 201 334 339 374 ETo mm 441 435 434 446 603 601 586 GD °C.day 1001 1001 1027 967 2950 2953 2947 CO2 ppm 400.55 400.55 400.55 400.55 400.55 400.55 400.55 Irri mm 0 0 0 0 0 0 0 Infilt mm 190 190 176 201 333 338 368 Runoff mm 0 0 0 0 1 1 6 Drain mm 0 0 0 0 0 0 0 Upflow mm 0 0 0 0 0 0 0 E mm 166 164 164 174 255 256 253 E/Ex % 70 71 69 71 81 82 83 Tr mm 125 126 109 126 155 155 143 TrW mm 125 126 109 126 155 155 143 Tr/Trx % 80 81 77 82 73 73 70 SaltIn ton/ha 0.000 0.000 0.000 0.000 0.000 0.000 0.000 SaltOut ton/ha 0.000 0.000 0.000 0.000 0.000 0.000 0.000 SaltUp ton/ha 0.000 0.000 0.000 0.000 0.000 0.000 0.000 SaltProf ton/ha 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Cycle days 93 94 93 92 112 112 113 SaltStr % 0 0 0 0 0 0 0 FertStr % 0 0 0 0 0 0 0 WeedStr % 0 0 0 0 0 0 0 TempStr % 21 21 24 22 0 0 0 ExpStr % 33 32 26 33 32 32 30 StoStr % 20 20 21 18 34 34 39 BioMass ton/ha 9.863 10.113 7.678 9.374 7.877 7.940 7.539 Brelative % 52 54 45 50 31 32 30 HI % 17.5 18.4 17.6 18.1 27.3 27.5 22.8 Yield ton/ha 1.725 1.865 1.350 1.698 2.154 2.179 1.716 WPet kg/m3 0.72 0.78 0.63 0.67 0.68 0.69 0.60 DayN 15 15 31 8 11 12 27 MonthN 8 8 8 8 9 9 9 YearN 2015 2015 2015 2015 2015 2015 2015

Day1, Start day of simulation run; Month1, Start month of simulation run; Year1, Start year of simulation run; Rain , Rainfall; ETo, Reference evapotranspiration; GD, Growing degrees; CO2, Atmospheric CO2 concentration; Irri, Water applied by

irrigation; Infilt, Infiltrated water in soil profile; Runoff, Water lost by surface runoff; Drain, Water drained out of the soil profile;

Upflow, Water moved upward by capillary rise; E, Soil evaporation; E/Ex, Relative soil evaporation (100 E/Ex); Tr, Total

transpiration of crop; TrW, Crop transpiration by weed infestation; Tr/Trx, Relative total transpiration (100 Tr/Trx); SaltIn, Salt infiltrated in the soil profile; SaltOut, Salt drained out of the soil profile; SaltUp, Salt moved upward by capillary rise from groundwater table; SaltProf, Salt stored in the soil profile; Cycle, Length of crop cycle; SaltStr, Soil salinity stress; FertStr, Soil fertility stress; WeedStr, Relative cover of weeds at canopy closure; TempStr, Temperature stress; ExpStr, Leaf expansion stress;

StoStr, Stomatal stress; Biomass, Cumulative biomass produced; Brelative Relative biomass; HI, Harvest Index adjusted for

inadequate photosynthesis and water stress; Yield, Yield (HI x Biomass); WPet, ET Water Productivity for yield part (kg yield produced per m3 water evapotranspired); DayN, End day of simulation run; MonthN, End month of simulation run; YearN, End year of simulation run.

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6.2.3 Conclusioni

In quessto studio il modello AquaCrop è stato impiegato per stimare i livelli di copertura fogliare, biomassa e raccolto di due specie agricole, in risposta al deficit di irrigazione in condizioni di clima sub-umido e semi-arido, tipico delle highlands keniane. Dati osservati sulle aree di test sono stati forniti dagli archivi della FAO e dall’USDA FAS (United States Department of Agriculture, Foreign Agricultural Service). La distanza fra stima ed osservazione dei raccolti di mais e grano nei siti in analisi (Fig. 6.7), è soddisfacente, con valori di R pari a 0.71 e 0.66 e MAE pari a 216 kg/ha e

650 kg/ha, rispettivamente per le due specie. Si può concludere che il modello AquaCrop può essere un valido strumento nella pianificazione e gestione delle attività agricole, in particolar modo considerando il fatto che il modello di simulazione richiede un numero limitato di parametri, in gran parte intuitivi ed espliciti, facilmente collezionabili (anche secondo procedure suscettibili di automazione) che, in molti casi, sono già disponibili. Non di meno le prestazioni del modello necessitano una più vasta ed approfondita validazione e valutazione, in funzione delle diverse possibili calibrazioni, e di una più ampia disponibilità di siti campione e specie agricole.

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